602LAN SUITE provides three methods of spam control. These methods can be used individually or in conjunction with each other to provide complete spam protection for your organization. The first two, DNSBL and SMTP blacklist, work by rejecting connections via a list of addresses linked to spamming. The third option, Bayesian filtering, rejects e-mail based on the content of the message.

DNSBL Summary

DNSBL is a method of blocking connections to your server by looking up the remote connection on a list of known spammers or net blocks. Many of these services are available at no cost, although some are subscription based services. This method rejects the actual connection before an e-mail is sent, so e-mail is never received from a blocked server.

Because it rejects connections rather than content, this method will not filter e-mail received via POP3 collection. This is because the e-mail collected via POP3 is not sent via SMTP to 602LAN SUITE, instead it is received via the POP3 protocol, and it originates from the same host (your remote POP3 server).

DNSBL Advantages 

An advantage of DNSBL is it blocks the actual connection from known spammers; it can save you bandwidth as well as CPU time and storage space to process and store the message. Additionally, there is little or no administration required, as these lists are usually managed by a third party. Since the entire server is blocked, this method is effective against all spam types, regardless of content.

DNSBL Disadvantages 

Some of the disadvantages include the fact that legitimate e-mail might be blocked if it originates from a server that is listed in the blacklist. Additionally, DNSBL has been subject to Denial of Service (DoS) attacks in the past, so you may experience a delay in receiving e-mail.

SMTP Blacklist Summary

Like DNSBL, the SMTP blacklist feature blocks the actual connection, so messages collected via POP3 cannot be filtered with this method. The SMTP blacklist is a great way to block individual e-mail or hosts from sending messages to your servers. This is an extremely flexible feature that allows you to block ANY e-mail address or host. The SMTP blacklist provides the most effective way to block a single user or host from sending e-mail to your 602LAN SUITE server.

SMTP Blacklist Advantages 

The greatest advantage is that you control the list of blocked addresses, rather than relying on the judgement of a third-party. Like the DNSBL method, it rejects the connection to your host, which can save bandwidth and network traffic. Another advantage is that it provides the flexibility to block just an e-mail address rather than an entire server, but it can block the entire server if you choose to do so.

SMTP Blacklist Disadvantages 

The greatest disadvantage to this method is that it takes a high-level of administration to build an effective blacklist. Additionally, blacklists are not effective against well-known spammer techniques such as address spoofing or relaying e-mail through other servers.

Bayesian Filtering Summary

Bayesian filtering is the only method that will work with mail collected from a remote server via POP3 collection. Bayesian filtering uses a mathematical algorithm to calculate a probability that a message is spam. It does so by learning from past messages that your organization considers legitimate and what it considers spam. Rather than rejecting the message based on the source, Bayesian filtering rejects the message based on the actual content.

Bayesian Filtering Advantages 

Advantages to Bayesian filtering is that it can be used to mark the message as spam, rather than rejecting the connection. This means it will allow you to review the messages individually to ensure that the messages are indeed spam. Other advantages include the use of adaptive technology to learn what is and is not spam. The more you train it, the better it becomes at identifying spam.

Bayesian Filtering Disadvantages 

Disadvantages of this method include the fact that it needs at least 100 legitamate and 100 spam messages to begin filtering. Once these messages have been forwarded to the learning addresses, users will need to forward received spam to reinforce Bayesian training.